FREE for non-commercial use - full version!
IMPORTANT NOTE ABOUT DOWNLOADING AI-TOOLKIT SOFTWARE: Please note that products from both companies Google and Microsoft use a wrong system to detect potentially dangerous downloads. These products are for example the internet browsers Chrome, Internet Explorer and operating system Windows 10. The problem is that they do not test if there is a valid digital signature in the downloaded file but they flag all downloads which are not downloaded frequently as potentially dangerous. Software (like the AI-TOOLKIT) which is updated frequently can never collect enough downloads to remove this message. You can disable this wrong behavior e.g. in Windows 10 by switching OFF the Windows Defender SmartScreen (Internet Options). This is perfectly safe to do if you have an antivirus software!
The AI-TOOLKIT is compatible with MS Windows 64-bit 7, 8, 10 and above and requires a CPU released after 2012 (including the AVX processor extension).
Homepage: AI-TOOLKIT
Download: AI-TOOLKIT Professional
What is included:
- AI-TOOLKIT Professional (flagship product)
- DeepAI Educational (educational deep neural network software with visualization of AI internals)
Get the serial number: In case you do not have a serial number then register on the AI-TOOLKIT Helpdesk (please fill in your real name and e-mail) and get automatically the serial number (FREE for non-commercial use - full version).
AI-TOOLKIT is an Artificial Intelligence (AI) Software Toolkit for easy training, testing and prediction of machine learning models and for creating machine learning flow.
The AI-TOOLKIT supports all 3 major forms of machine learning: supervised, unsupervised and reinforcement learning! No programming skills are needed at all for building and using state of the art machine learning models!
Easy to use and contains several types of machine learning models which can be used separately or connected to each other (ML Flow). There is also a built-in very fast SQL database in order to make the storage of your machine learning data compact and easy. The database supports several GB's of data storage and several databases can be used even in one project.
The following major machine learning models and techniques are supported by the AI-TOOLKIT:
- Supervised Learning - Support Vector Machine Model
- Supervised Learning - Random Forest Classification Model
- Supervised Learning - Feedforward Neural Network Regression Model
- Supervised Learning - Feedforward Neural Network Classification Model
- Supervised Learning - Convolutional Feedforward Neural Network Classification Model
- Supervised Learning - Recurrent Neural Network Regression Model (RNN_R)
- Supervised Learning - Recurrent Neural Network Classification Model (RNN_C)
- Unsupervised Learning - KMeans Classification Model
- Unsupervised Learning - MeanShift Classification Model
- Unsupervised Learning - DBScan Classification Model
- Unsupervised Learning - Hierarchical Classification Model
- Reinforcement Learning - Deep Q-Learning (Neural Network)
- Dimensionality Reduction with PCA (Principal Component Analyzes)
- Recommendation with Explicit Feedback (Collaborative Filtering) (CFE)
- Recommendation with Implicit Feedback (Collaborative Filtering) (CFI)
You can use the built-in machine learning models separately (training and prediction/inference) or you can build a larger AI system in which several AI models are working together in a flow. Working together in a flow means that one machine learning model may use the output of one or more other machine learning models in a continuous running AI system.
There are several easy to apply machine learning model templates built-in which makes building a complex AI model very easy by using just some mouse clicks. You can train and test your models easily.
You can import any delimited data file into the database. You can also import images which will be converted automatically to machine learning data and saved into the database.
If you select the "Automatically Convert Categorical or Text values" option then categorical values will be automatically converted to numbers with one of the following options (based on your choices per column):
- integer encoding,
- one-hot encoding (increases the number of features!),
- binary encoding (increases the number of features!).
If you select the "Resample for Imbalance Reduction (Classification only!)" option then the data will be automatically resampled in order to correct the class imbalance in the data. The AI-TOOLKIT uses a combination of state of the art resampling methods in order to provide the best possible resampling (noise removal + undersampling of majority classes + oversampling of not majority classes) and not just duplicating or removing records.
There is an easy to use database editor which can be used to view and edit all AI-TOOLKIT databases. The database editor and the AI-TOOLKIT both support encrypted databases in case you need to secure your data.
All machine learning models are optimized for maximum performance and accuracy.
Built-in Tools
There are also several built-in professional machine learning tools and applications: Image editor, Audio editor, Face Recognition app, Speaker Recognition app, Fingerprint Recognition app, etc.
For more information please read the help of each sub-module in the right sidebar of the software.
Visit the AI-TOOLKIT website for more information and training video's.
AI-TOOLKIT and the AI-TOOLKIT Artificial Intelligence Engine are (C) Copyright 2016-present Zoltan Somogyi, All Rights Reserved. Read the license "License.md".